CAREER: Motion Capabilities for Autonomous Mobile Manipulation

职业生涯：自主移动机械手的运动能力摘要工业界和学术界的共同努力导致了高度先进的类人机器人和移动机械手的设计和建造。这些机构将灵活的操作能力与机动性结合在一起，并配备了多模式传感器套件。这些复杂机构的自主运动受到许多约束，每个约束都需要考虑特定频率的反馈。研究人员提出了一种新的运动生成方法，解决了运动约束及其反馈约束。在频谱的低端，研究人员提出了将主动学习和效用理论的技术应用于全局运动规划。这些技术允许利用任何真实世界运动规划问题中固有的结构来提高运动规划的效率。所得到的规划方法将满足自主移动操作的反馈要求。为了获得关于环境状态的充分反馈，感知信息由新的传感和建模技术提供，这也将作为这一努力的一部分而开发。为了解决需要高频反馈的运动约束，研究人员提出将多目标控制方法与约束满足规划方法相结合。这些规划方法克服了基于控制的运动生成容易陷入局部极小的缺点。由此产生的运动生成的整体方法解决了自主移动操纵的运动要求，向非结构化环境中的类人机器人和移动机械手的自主操作迈进了一大步。

CAREER: Motion Capabilities for Autonomous Mobile ManipulationAbstractConcerted efforts in industry and academia have lead to the design and construction of highly advanced humanoid robots and mobile manipulators. These mechanisms combine dexterous manipulation capabilities with mobility and are equipped with multi-modal sensor suites. Autonomous motion of these complex mechanisms is subject to a multitude of constraints, each requiring the consideration of feedback at a specific frequency. The investigator proposes to devise a novel motion generation generation approach that addresses motion constraints and their feedback constraints. At the low end of the frequency spectrum, the investigator proposes the application of techniques from active learning and utility theory to global motion planning. These techniques permit the exploitation of structure inherent in any real-world motion-planning problem to increase the efficiency of motion planning. The resulting planning methods will satisfy the feedback requirements of autonomous mobile manipulation. To obtain adequate feedback about the state of the environment, perceptual information is provided by novel sensing and modeling techniques, which will also be developed as part of this effort. To address motion constraints that require high-frequency feedback, the investigator proposes to combine multi-objective control methods with planning approaches for constraint satisfaction. These planning methods overcome the susceptibility of control-based motion generation to local minima. The resulting overall approach to motion generation addresses the motion requirements of autonomous mobile manipulation, offering a significant advance towards the autonomous operation of humanoid robots and mobile manipulators in unstructured environments.